The long-term goal of this proposal is to develop effective integrated computational and experimental approaches to identify interactions between proteins and major metabolites on a proteomics scale. The proposed approach allows rapid identification of ligand binding proteins on a proteomics scale and constructing protein-metabolite interaction network, which will provide crucial information for understanding biological systems. As a model case, we will identify NAD+ and NADP+ binding proteins in the E. coli proteome. In particular, the following specific aims are proposed: (1) To develop a set of computational methods for predicting proteins that bind to metabolites. We employ both sequence- based and structure-based methods. The sequence-based methods we will develop and employ include our novel function prediction methods, PFP and its variant, which are shown to have higher sensitivity and higher function assignment coverage than conventional methods. Structure-based methods include fast local protein surface shape comparison method, which directly compare shape and physicochemical property of local surface regions. (2) To apply energetics-based target identification approach to efficiently screen proteins that bind to metabolites. Proteins stabilized upon binding to NAD+ and NADP+ will be identified in a E. coli lysate by combining a brief incubation with a protease and quantitative mass spectrometry. Proteins identified by either computational or experimental methods will be cross-validated by the complementary approaches. Successful completion of this project will establish methodology for systematic identification of proteins that bind to specific metabolites and thus will enable us to provide interaction network of proteins and metabolites in cells. The methodology to be developed and the resulting interaction network will assist in the early stages of drug discovery, and hence the proposed project could have significant therapeutic utility.

Public Health Relevance

The goal of the project is the development of intergrated computational and experimental approach to determine interactions between proteins and major matabolites in cells on a systems level. The proposed approach will allow rapid identification of ligand binding proteins on a proteomics scale and will enable the construction of protein-metaboolite interaction networks. The outcome of this project will provide information crucial in understanding biological systems and useful in hypothesis generation in the early stages of drug discovery.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Preusch, Peter C
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Purdue University
Schools of Arts and Sciences
West Lafayette
United States
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Sit, Atilla; Kihara, Daisuke (2014) Comparison of image patches using local moment invariants. IEEE Trans Image Process 23:2369-79
Peterson, Lenna X; Kang, Xuejiao; Kihara, Daisuke (2014) Assessment of protein side-chain conformation prediction methods in different residue environments. Proteins 82:1971-84
Esquivel-Rodriguez, Juan; Filos-Gonzalez, Vianney; Li, Bin et al. (2014) Pairwise and multimeric protein-protein docking using the LZerD program suite. Methods Mol Biol 1137:209-34
Kim, Hyungrae; Kihara, Daisuke (2014) Detecting local residue environment similarity for recognizing near-native structure models. Proteins 82:3255-72
Olek, Anna T; Rayon, Catherine; Makowski, Lee et al. (2014) The structure of the catalytic domain of a plant cellulose synthase and its assembly into dimers. Plant Cell 26:2996-3009
Padilla-Sanchez, Victor; Gao, Song; Kim, Hyung Rae et al. (2014) Structure-function analysis of the DNA translocating portal of the bacteriophage T4 packaging machine. J Mol Biol 426:1019-38
Xiong, Yi; Esquivel-Rodriguez, Juan; Sael, Lee et al. (2014) 3D-SURFER 2.0: web platform for real-time search and characterization of protein surfaces. Methods Mol Biol 1137:105-17
Hu, Bingjie; Zhu, Xiaolei; Monroe, Lyman et al. (2014) PL-PatchSurfer: a novel molecular local surface-based method for exploring protein-ligand interactions. Int J Mol Sci 15:15122-45
Radivojac, Predrag; Clark, Wyatt T; Oron, Tal Ronnen et al. (2013) A large-scale evaluation of computational protein function prediction. Nat Methods 10:221-7
Esquivel-Rodriguez, Juan; Kihara, Daisuke (2013) Computational methods for constructing protein structure models from 3D electron microscopy maps. J Struct Biol 184:93-102

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